基于图像分类的全局动态调光算法

Global Dimming Algorithm Based on Image Classification

针对液晶显示能效不高、对比度低的问题,提出了一种基于图像分类的全局动态调光算法。鉴于亮度和对比度是液晶显示的两个重要性能指标,提出了基于亮度和对比度的图像分类方法。背光调光水平由输入图像的类别、灰度平均值以及灰度最大值与灰度平均值的差值决定。液晶像素补偿基于S曲线,曲线方程中的参数根据输入图像特征值和图像类别决定。对60幅图像的仿真结果表明:平均背光节能达到了19%,静态对比度提高了143%。开发了采用本调光算法的液晶电视,与没有采用本调光算法的电视相比,整机平均节能达到了12.9%,静态对比度提高了43.18%。

To tackle the problems of low power efficiency and low contrast of liquid crystal display, a global dimming algorithm based on image classification is proposed. As brightness and contrast are two important display parameters, the paper takes use of these two parameters to classify the input images. Backlight dimming level is determined by image category, the average luminance and the difference between the average and maximum grayscales of all subpixels. The S-shaped curve is generated based on the characteristic value and the image category of input image to compensate liquid crystal pixels. For 60 images, the simulation results show that the average backlight power consumption is reduced by 19% and the static contrast ratio is improved by 143%. The prototype is developed based on the dimming algorithm. Compared with the LCD TV without applying the dimming algorithm, the practical results show that the average power consumption is reduced by 12.9% and the static contrast ratio is improved by 43.18%.